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BrunoSan Intelligence Concierge

search_capabilities

Search the whole BrunoSan network for what an agent is trying to do.

Ranking is deterministic over SSOT descriptions, a documented routing vocabulary and LIVE tool names/descriptions/schemas. Returns concrete tool candidates, not merely domain names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesNatural-language goal or capability, e.g. 'critical CVEs', 'citation network', 'EU AI Act sanctions'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and does meaningful work: it discloses that ranking is deterministic, that it operates over SSOT descriptions and live tool metadata, and that it returns candidates rather than domain names. It does not cover potential rate limits or auth expectations, but those are less critical for a search-style tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the first sentence states the agent-facing purpose, and the following sentences add only high-value behavioral detail. No sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is reasonably complete for a simple search tool, but with no output schema it only vaguely promises 'concrete tool candidates' without specifying the return shape, ranking scores, or how the limit parameter shapes results. It also does not advise on follow-up actions like inspecting a returned tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: the query parameter is described with examples, and the tool description reinforces that it accepts a natural-language goal. The limit parameter is not described in the tool description, though its default, minimum, and maximum in the schema make its behavior partly inferable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Search the whole BrunoSan network for what an agent is trying to do.' It further distinguishes itself by saying it returns 'concrete tool candidates, not merely domain names,' which separates it from domain-listing siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies use when an agent has a natural-language goal and needs capability routing, but it does not explicitly name alternatives such as inspect_tool, list_intelligence_domains, or plan_intelligence_route, nor does it state when not to use them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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